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SparkApplication · Apache

CVE-2023-32007

HIGH · 8.8 CVSS v3.1 Published 2023-05-02
Fix available
A fix is available. Upgrade to after 3.2.1 or later.
See remediation →
94/100
Remediation priority · Urgent
High EPSS Remotely reachable Zero-click

Official description Straight from the sourceThe vendor's or NVD's own wording, published unedited. Authoritative, but often terse — it says what broke, rarely what to do.

NVD · unedited
** UNSUPPORTED WHEN ASSIGNED ** The Apache Spark UI offers the possibility to enable ACLs via the configuration option spark.acls.enable. With an authentication filter, this checks whether a user has access permissions to view or modify the application. If ACLs are enabled, a code path in HttpSecurityFilter can allow someone to perform impersonation by providing an arbitrary user name. A malicious user might then be able to reach a permission check function that will ultimately build a Unix shell command based on their input, and execute it. This will result in arbitrary shell command execution as the user Spark is currently running as. This issue was disclosed earlier as CVE-2022-33891, but incorrectly claimed version 3.1.3 (which has since gone EOL) would not be affected. NOTE: This vulnerability only affects products that are no longer supported by the maintainer. Users are recommended to upgrade to a supported version of Apache Spark, such as version 3.4.0.

Technical summary Written by usOur analysis, written from the advisory, the CVSS vector and the affected-version data. It adds context the advisory leaves out, and never invents facts that are not in the source.

dbcve analysis · high confidence

Apache Spark UI with ACLs enabled (spark.acls.enable) has a code path in HttpSecurityFilter that allows impersonation via arbitrary username input. This input reaches a permission check function that constructs and executes a Unix shell command, leading to arbitrary command execution as the Spark user. This is a bypass/revisit of CVE-2022-33891 that was incorrectly marked as fixed in version 3.1.3.

MitigationUpgrade to Apache Spark 3.4.0 or later where this vulnerability is fixed. If upgrading is not immediately feasible, verify ACLs are disabled (spark.acl.enable=false) and ensure the Spark UI is not exposed to untrusted networks.

Verify against the referenced sources before acting — the references below are authoritative for this CVE, this summary is not.

Affected products & versions What the vendor confirmedThe version ranges the vendor confirmed as vulnerable. If your version sits inside a range here, treat yourself as exposed until you have upgraded.

NVD · CPE data
SparkApplication
Affected:<= 3.0.3>= 3.1.1, <= 3.1.3>= 3.2.0, <= 3.2.1

CVSS breakdown How the score is builtThe industry scoring standard. It rates how the flaw is reached, what it takes to exploit, and what an attacker gains — the score is derived from those, not the other way round.

From the vector
Attack vector
Network
Complexity
Low
Privileges
Low
User interaction
None
Scope
Unchanged
Confidentiality
High
Integrity
High
Availability
High

CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H

Am I affected? How to checkSteps we derive from the advisory and the affected-version data, so you can decide whether this CVE reaches your setup. They are a guide, not a scan — your own configuration is the authority.

dbcve checks

Work through these to decide whether this CVE applies to you.

  1. Identify installed Apache Spark version
    Run 'spark-submit --version' or check the Spark version from the installation directory (e.g., ls /usr/local/spark or ls /opt/spark)
    Affected if The version is 3.0.3 or lower, between 3.1.1 and 3.1.3 inclusive, or between 3.2.0 and 3.2.1 inclusive
  2. Verify ACL configuration
    Check Spark configuration files (spark-defaults.conf, spark-env.sh) or run a Spark job with 'spark.sparkContext.getConf.get("spark.acls.enable")' and 'spark.sparkContext.getConf.get("spark.acl.enable")' to see if ACLs are enabled
    Affected if Either spark.acls.enable or spark.acl.enable is set to true
  3. Confirm vulnerable code path is reachable
    Check if the Spark UI (port 4040 by default, or configured port) is accessible. Review HTTP endpoint exposure via spark.ui.filters or security filters configuration
    Affected if The Spark UI is exposed to network and ACLs are enabled (both conditions must be true)

You are affected if your Spark version falls within the vulnerable ranges AND ACLs are enabled AND the Spark UI is network-accessible, which together allow arbitrary command execution through the HttpSecurityFilter impersonation flaw.

Generated from the published advisory. Verify against your own configuration.

Check your environment

Paste your version and any relevant configuration and it will be compared against the affected criteria above. Do not include secrets or credentials.

AI-assisted, checked against the advisory. Informational, not a guarantee.

Remediation Closing itWhat it takes to close this. Where a vendor fix exists we point at it; where none exists we say so plainly, and can build one. Effort estimates are scoped from the advisory, not from your codebase.

dbcve · scoped
Upgrade available Upgrade to a release after 3.2.1
Interim mitigation

Upgrade to Apache Spark 3.4.0 or later where this vulnerability is fixed. If upgrading is not immediately feasible, verify ACLs are disabled (spark.acl.enable=false) and ensure the Spark UI is not exposed to untrusted networks.

Recommended fix High confidence

3.4.0

  1. 1. Download Apache Spark 3.4.0 or later from the official Apache Spark distribution (https://spark.apache.org/downloads.html)
  2. 2. Back up all existing Spark configuration files (spark-defaults.conf, spark-env.sh, etc.) and any custom applications or data
  3. 3. Stop all running Spark services and applications
  4. 4. Extract the new Spark 3.4.0 binaries to the desired installation directory
  5. 5. Restore or migrate the backed-up configuration files to the new installation
  6. 6. Verify that spark.acls.enable is properly configured if ACLs are needed, or disable ACLs if not required
  7. 7. Start the Spark services and verify the UI is accessible
  8. 8. Test that applications run correctly and the UI functions properly
Caveat Major version upgrades may introduce API changes; review Spark 3.4.0 release notes for any breaking changes in your specific use case

Generated from the published advisory — verify against the referenced sources before acting.

Fix this in Spark Scoped from the published advisory
  • Consultation4.0 h
  • Implementation8.0 h
  • Testing6.0 h
  • Review / QA2.0 h
20.0 hours of engineering $3,500
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References Go to the primary sourcePrimary sources — vendor advisories, patches and trackers. Where our summary and a reference disagree, the reference wins.

Primary sources

Practitioner notes

Contributed

Peer-ranked notes from engineers who’ve handled CVE-2023-32007 in production — separate from our analysis above.

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What this is

A place for practitioners to share what actually worked: a mitigation you’ve tested, a configuration change, a version- or environment-specific caveat, or a link to a verified patch. The most useful notes rise to the top as peers upvote them, so the signal stays high.

What belongs here
  • Verified mitigations, workarounds, and config changes
  • Version or environment caveats, and links to real fixes
  • No weaponised exploit code, or anything meant to cause harm
  • No spam, self-promotion, credentials, or personal data